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Translational Science Model, the Organizational Setting and the Population

Translational Science Model

The Ottawa Model of Research Use (OMRU) is a translational science model that can be very helpful for the proposed project, which is dedicated to reducing blood sugar in diabetic patients with the help of a patient engagement tool by Smith et al. (2017). Initially, it was planned to consider Lewin’s change model, but OMRU proved to be very suitable for the project. Indeed, in its original and revised forms (Graham & Logan, 2004; Logan & Graham, 1998), OMRU is especially appropriate for transferring knowledge, which is precisely what the project is going to involve.

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The model incorporates six elements, and the first three are the innovation, which is the patient engagement tool by Smith et al. (2017), the adopters, who are diabetic patients, and the environment, which is a primary care and prevention center (Graham & Logan, 2004; Logan & Graham, 1998). Indeed, the adopters in this situation are patients, which is in line with the idea of engaging patients in their care (Bombard et al., 2018; Kim et al., 2018; Park & Giap, 2020).

The first three elements are united by the action that needs to be applied to them, which is assessment. Then, the elements of implementation and adoption are to be monitored, with the final element of outcomes being evaluated (Logan & Graham, 1998). For the project, the adoption process will be monitored through patient journals, and the outcomes will include blood sugar.

According to Graham and Logan (2004), the model is implemented in six steps, most of which are meant to perform the actions of assessment, monitoring, and evaluation, and the rest of which are the prerequisites for those activities. Thus, the framework incorporates the critical aspects of the procedures that are going to be involved in the project and the recommendations on what to do with them. The model is also multidirectional and dynamic (Graham & Logan, 2004), which will make it flexible. Overall, there are multiple benefits to the model, and its key premises fit the project, which is why it was chosen.

Organizational Setting

The project will take place at a prevention and primary care medical office that employs ten people and provides services to roughly 25-30 adult patients a day, which averages to approximately 600 visits per month. The most provided service is general checkups; the most common conditions include diabetes, osteoarthritis, heart disease, chronic obstructive pulmonary disease, seasonal allergies, and dermatitis. An average patient of the office is middle-aged or nearing older age and has one or two chronic health conditions. Other than that, the patient population is rather diverse, especially in terms of race/ethnicity and socioeconomics.

Population Description

In the proposed project, the population of interest is adults with diabetes, which is a very widespread condition (Zimmet, Alberti, Magliano, & Bennett, 2016). This group constitutes a rather large portion of the settings’ patients, which will make approaching them easier. It is planned to involve 50 patients, which is feasible with the number of patients that are seen at the office. The patients will be recruited with the help of leaflets that will be given out by their healthcare providers with an explanation that participation is optional and holds limited risks. Informed consent documents will be provided to those who contact the researcher, and they will contain all the details about the project.

The primary characteristics of the participants will include being a patient of the setting center, having diabetes, and being interested in participating. People who cannot give consent because of any health issues are going to be excluded, and the providers will be instructed to avoid providing them with leaflets. The information about the types of treatment of the participants will be collected, and currently, it is not planned to exclude any of them since statistical tests should help to determine statistically significant pretest-posttest changes (Polit & Beck, 2017). No other exclusion criteria will be employed, and people with different backgrounds will be recruited.

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Bombard, Y., Baker, R., Elaina, O., Bhatia, P., Casalino, S., Onate, K.,… Pomey, M. (2018). Engaging patients to improve quality of care: A systematic review. Implementation Science, 13(1), 1-22. Web.

Graham, I. D., & Logan, J. (2004). Translating research-innovations in knowledge transfer and continuity of care. Canadian Journal of Nursing Research Archive, 36(2), 89-103.

Kim, J. M., Suarez-Cuervo, C., Berger, Z., Lee, J., Gayleard, J., Rosenberg, C.,… Dy, S. (2018). Evaluation of patient and family engagement strategies to improve medication safety. The Patient – Patient-Centered Outcomes Research, 11(2), 193-206. Web.

Logan, J., & Graham, I. D. (1998). Toward a comprehensive interdisciplinary model of health care research use. Science Communication, 20(2), 227–246.

Park, M., & Giap, T. (2020). Patient and family engagement as a potential approach for improving patient safety: A systematic review. Journal of Advanced Nursing, 76(1), 62-80. Web.

Polit, D.F., & Beck, C.T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Lippincott, Williams & Wilkins.

Smith, K., Baker, K., Wesley, D., Zipperer, L., Clark, M. D., Hanneke, C. R.,… Goeschel, C. A. (2017). Guide to improving patient safety in primary care settings by engaging patients and families. Web.

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Zimmet, P., Alberti, K., Magliano, D., & Bennett, P. (2016). Diabetes mellitus statistics on prevalence and mortality: Facts and fallacies. Nature Reviews Endocrinology, 12(10), 616-622. Web.

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